Engagement signal generation and analysis

Patent metadata

Field	Value
Publication number	US-2022351034-A1
Application number	US-202117245948-A
Country	US
Kind code	A1
Filing date	Apr 30, 2021
Priority date	Apr 30, 2021
Publication date	Nov 3, 2022
Grant date	—

Abstract

Engagement signals may be generated and analyzed based on user interactions with documents, particularly in a collaboration environment. The user interactions may generate raw collaboration signals that may be received and processed into cleaned collaboration signals. For example, noise may be removed from the raw collaboration signals to generate the cleaned collaboration signals. The cleaned collaboration signals may be grouped into engagement signals, where each engagement signal represents an individual event or engagement event of the user with the document. The grouping may be based on boundary signals, time frames, and/or any other reasonable limiting element. Each of the engagement signals may be classified into one of several engagement types based on the cleaned collaboration signals in the engagement signal. The engagement signals may then be analyzed to make determinations, recommendations, or the like regarding one or more users of the document, the document content, or the like.

First claim

What is claimed is:

1 . A computer-implemented method for generating and analyzing engagement signals, the method comprising:
receiving raw collaboration signals generated based on a user interacting with a document; processing the raw collaboration signals into cleaned collaboration signals; grouping the cleaned collaboration signals into engagement signals, each engagement signal representing an individual event; and classifying each of the engagement signals into one of a plurality of engagement types based on the cleaned collaboration signals in the engagement signal.

2 . The computer-implemented method of claim 1 , wherein the raw collaboration signals comprise at least one of document open signals, window minimize signals, window focus signals, document close signals, window maximize signals, input activity signals, or a combination thereof.

3 . The computer-implemented method of claim 1 , wherein processing the raw collaboration signals into cleaned collaboration signals comprises aggregating the raw collaboration signals to remove noise.

4 . The computer-implemented method of claim 1 , wherein grouping the cleaned collaboration signals into engagement signals comprises:
identifying boundary signals in the cleaned collaboration signals that indicate a beginning and an end of an event; and combining the cleaned collaboration signals occurring between the boundary signals into the engagement signal.

5 . The computer-implemented method of claim 1 , wherein grouping the cleaned collaboration signals into engagement signals comprises:
providing the cleaned collaboration signals to a neural network configured to identify boundary signals for events; and receiving boundary signals that indicate a beginning and end of an event as output from the neural network.

6 . The computer-implemented method of claim 1 , wherein classifying each of the engagement signals into one of the plurality of engagement types comprises:
providing each of the engagement signals into an advanced intelligence classifier; and receiving an engagement type as output from the advanced intelligence classifier for each of the engagement signals.

7 . The computer-implemented method of claim 1 , wherein the engagement types comprise editing, viewing, reviewing, authoring.

8 . The computer-implemented method of claim 1 , further comprising:
assigning a collaboration role to the user for the document based on the classified engagement signals.

9 . The computer-implemented method of claim 1 , further comprising:
providing recommendations to a contributor of the document based on analyzing classified engagement signals of a plurality of users of the document.

10 . The computer-implemented method of claim 1 , further comprising:
sending a notification of an action related to the document to the user of the document based at least in part on the classified engagement signals.

11 . A system comprising:
one or more processors; and a memory having stored thereon instructions that, upon execution by the one or more processors, cause the one or more processors to:
receive raw collaboration signals generated based on a user interacting with a document;
process the raw collaboration signals into cleaned collaboration signals;
group the cleaned collaboration signals into engagement signals, each engagement signal representing an individual event; and
classify each of the engagement signals into one of a plurality of engagement types based on the cleaned collaboration signals in the engagement signal.

12 . The system of claim 11 , wherein the raw collaboration signals comprise at least one of document open signals, window minimize signals, window focus signals, document close signals, window maximize signals, input activity signals, or a combination thereof.

13 . The system of claim 11 , wherein the instructions to process the raw collaboration signals into cleaned collaboration signals comprises instructions that, upon execution by the one or more processors, cause the one or more processors to aggregate the raw collaboration signals to remove noise.

14 . The system of claim 11 , wherein the instructions to group the cleaned collaboration signals into engagement signals comprise further instructions that, upon execution by the one or more processors, cause the one or more processors to:
identify boundary signals in the cleaned collaboration signals that indicate a beginning and an end of an event; and combine the cleaned collaboration signals occurring between the boundary signals into the engagement signal.

15 . The system of claim 11 , wherein the instructions to group the cleaned collaboration signals into engagement signals comprises instructions that, upon execution by the one or more processors, cause the one or more processors to:
provide the cleaned collaboration signals to a neural network configured to identify boundary signals for events; and receive boundary signals that indicate a beginning and end of an event as output from the neural network.

16 . The system of claim 11 , wherein the instructions to classify each of the engagement signals into one of the plurality of engagement types comprises instructions that, upon execution by the one or more processors, cause the one or more processors to:
provide each of the engagement signals into an advanced intelligence classifier; and receive an engagement type as output from the advanced intelligence classifier for each of the engagement signals.

17 . The system of claim 11 , wherein the engagement types comprise editing, viewing, reviewing, authoring.

18 . The system of claim 11 , wherein the instructions comprise further instructions that, upon execution by the one or more processors, cause the one or more processors to:
assign a collaboration role to the user for the document based on the classified engagement signals.

19 . The system of claim 11 , wherein the instructions comprise further instructions that, upon execution by the one or more processors, cause the one or more processors to:
provide recommendations to a contributor of the document based on analyzing classified engagement signals of a plurality of users of the document.

20 . The system of claim 11 , wherein the instructions comprise further instructions that, upon execution by the one or more processors, cause the one or more processors to:
send a notification of an action related to the document to the user of the document based at least in part on the classified engagement signals.

Assignees

• Microsoft Technology Licensing Llc

Inventors

• Lorrain-Hale Theo
• Tierney William D
• Liu Feng
• Milvaney Douglas Lane
• Knoertzer Manon

Classifications

• G06F18/2431

  Multiple classes · CPC title

• G06F18/40

  Software arrangements specially adapted for pattern recognition, e.g. user interfaces or toolboxes therefor · CPC title

• G06N3/04

  Architecture, e.g. interconnection topology · CPC title

• G06Q10/00 Primary

  Administration; Management · CPC title

• G06N3/08 Primary

  Learning methods · CPC title